Isaac Newton Institute for Mathematical Sciences

Neural Networks and Machine Learning

A Newton Institute EC Summer School

PROBABILISTIC GRAPHICAL MODELS

1 - 5 September 1997

Organisers: C M Bishop (Aston) and J Whittaker (Lancaster)

Probabilistic graphical models provide a very general framework for
representing complex probability distributions over sets of variables.
A powerful feature of the graphical model viewpoint is that it unifies
many of the common techniques used in pattern recognition and machine learning
including neural networks, latent variable models, probabilistic expert
systems, Boltzmann machines and Bayesian belief networks. Indeed, the increasing
interactions between the neural computing and graphical modelling communities
have resulted in a number of powerful new ideas and techniques. The conference
will include several tutorial presentations on key topics as well as advanced
research talks.

This instructional conference will form a component of the Newton Institute
programme on Neural
Networks and Machine Learning, organised by CM Bishop, D Haussler,
GE Hinton, M Niranjan and LG Valiant.

Location and Costs: The conference will take place in the Isaac
Newton Institute and accommodation for participants will be provided
at Wolfson Court, adjacent to the Institute. The conference package costs
£270 which includes accommodation from Sunday 31 October to Friday
5 September, together with breakfast, lunch during the days that the lectures
take place and evening meals.